Infopaket

Applied mathematical statistics

ВБ 1.04

Вибіркова дисципліна для ОП

First

2022/2023

6 Semester

3

The purpose of the discipline - to acquaint students with statistical methods and apply them to economic and physical data for analysis, estimation of parameters and characteristics, modeling.

Full-time form

The discipline "Applied Mathematical Statistics" is based on a series of disciplines of professional and practical training of the bachelor, namely: "Probability Theory", "Statistical Radiophysics", "Object Oriented Programming". Prerequisites: the student must know: the basics of probability theory and mathematical statistics, the basics of programming. the student must be able to: operate with random variables and processes, apply statistical methods in practice, program.

The discipline "Applied Mathematical Statistics" allows the student to navigate in modern problems of applied statistics and to study the software system, which is a tool for solving such problems. As you know, statistical methods are the most widely used mathematical tool for professionals in economics. The course "Applied Mathematical Statistics" consists of sections "Basic concepts of R", "Chi-square and Kolmogorov criterion", "Linear multiple regression", "One-way and multifactor variance analysis", "Nonlinear regression", "Sample surveys". Each of these sections allows us to study certain statistical methods of data analysis, both from a theoretical point of view and from a practical point of view, based on the programming environment (programming language) R.

1. Р.Є. Майборода «Комп’ютерна статистика.» Підручник. - К., ВПЦ «Київський університет», 2019. https://probability.knu.ua/userfiles/mre/cscolor.pdf 2. Р.Є. Майборода, О.В. Сугакова «Аналіз даних за допомогою пакету R». Навчальний посібник – К., 2015. http://matphys.rpd.univ.kiev.ua/wp/wp-content/uploads/2016/12/Statistics_with_R.pdf 3. M.D. Ugarte, A.F. Militino, A.T. Arnholt. Probability and statistics with R. – Boca Raton, London, New York: CRC Press, Taylor&Francis Group, 2008. 4. О.І. Черняк, О.В. Комашко, А.В. Ставицький, О.В. Баженова «Економетрика» - ВПЦ «Київський університет», 2009. 5. О.І. Василик, Т.О. Яковенко. Лекції з теорії і методів вибіркових обстежень - К., ВПЦ «Київський університет», 2010. https://probability.knu.ua/userfiles/mre/cscolor.pdf

This course provides classes in the amount of: lectures - 30 hours, practical classes - 28 hours; individual work of students in the amount of 62 hours is also planned. Methods of semester control: tests conducted during practical classes and individual homework. Final control is exam.

The level of achievement of all planned learning outcomes is determined by the results of laboratory work. Contribution of learning outcomes to the final assessment, provided that they are mastered at the appropriate level: 1.1 - 1.10 [knowledge] - up to 45%; 2.1 - 2.3 [skills] - up to 45%; 3.1-3.2 [communication] - up to 5%; 4.1 [autonomy and responsibility] - up to 5%. Forms of estimation: - semester assessment: The academic semester has one module. The student must complete and pass four laboratory works. Mandatory for admission to the exam is: to score at least 36 points during the semester. - final assessment (in the form of an exam): the form of the exam is written-oral. The task for the exam consists of 2 questions and two tasks, questions are evaluated on 10 points. In total, you can get from 0 to 40 points for the test. The condition for achieving a positive grade for the discipline is to obtain at least 60 points, the grade for the exam can not be less than 24 points.

Ukranian